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Keywords: bayesian inference
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Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-203941-MS
... analysis to generate a set of ordinary differential equations is novel. The extension of previously described probabilistic forecasting to a generalised model has many possible applications within and outside the oil and gas industry, and is not restricted to reservoir simulation. bayesian inference...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-203907-MS
... are able to match statistics for a simple flow problem on the fine grid with high accuracy and at much lower cost on a scale of coarser grids. bayesian inference sampler artificial intelligence upstream oil & gas posterior distribution iteration time scaling method reservoir simulation...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-203950-MS
... subsurface storage climate change bayesian inference evolutionary algorithm sequestration wheeler probabilistic surrogate acquisition function optimization problem bayesian optimization optimization application gaussian process upstream oil & gas simulation function evaluation carbon...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-204008-MS
... ] . The posterior probability density function (PDF) of uncertain model parameters x by conditioning to production data ( d obs ) can be formulated within the Bayesian inference framework ( Oliver, Reynolds, and Liu, 2008 ; Tarantola, 2005 ) as, (3) p ( x | d o b s ) = c p prior...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, October 26, 2021
Paper Number: SPE-204006-MS
... agreeing with available measurements and thus extend partial point-wise estimates to full tensor fields compatible with the physics of the site. reservoir characterization reservoir geomechanics structural geology optimization problem machine learning bayesian inference model uncertainty pore...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193844-MS
... reservoir simulation Artificial Intelligence Bayesian Inference Reservoir Characterization Upstream Oil & Gas model parameter ensemble ensemble Kalman filter impedance facies distribution probability distribution reservoir model information geoscience history matching well location...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193838-MS
...) outperform the others in terms of the quality of the estimated parameters and the prediction accuracy (reliability of the calibrated models). Case Study machine learning history matching Bayesian Inference model error reservoir simulation coverage probability posterior distribution prediction...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193830-MS
... to optimizing production processes in the field. Reservoir Characterization Artificial Intelligence complex reservoir Bayesian Inference natural fracture network machine learning hydraulic fracturing Upstream Oil & Gas geomechanics mikelić hydraulic fracture equation natural fracture...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, April 10–11, 2019
Paper Number: SPE-193910-MS
... The methods selected for the benchmarking study presented in this work are based on Bayesian inference. The adequacy of using Bayesian based methods for uncertainty quantification in AHM is not discussed here. The interested reader is referred to Vink et al. (2016) for a discussion...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, February 20–22, 2017
Paper Number: SPE-182684-MS
... are presented to establish the validity of the method. The performance of the new MCMC algorithm is compared with random walk MCMC and is also compared with population MCMC for a target pdf which is multimodal. reservoir simulation posterior distribution Bayesian Inference proposal distribution...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, February 20–22, 2017
Paper Number: SPE-182602-MS
... matrix formulation history matching sorensen solver performance profile subproblem trust region solver newton-raphson method bayesian inference memory usage Introduction Because of limited access to the subsurface reservoir, reservoir properties such as permeability and porosity have...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, February 20–22, 2017
Paper Number: SPE-182599-MS
... posterior distribution Hessian matrix Bayesian Inference uncertainty quantification result conditional realization measurement error modeling error forecast spurious uncertainty reduction realization reservoir model workflow MAP estimate mismatch model parameter matrix uncertain model...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, February 20–22, 2017
Paper Number: SPE-182639-MS
... constraint RML method machine learning reservoir simulation objective function unconditional realization Artificial Intelligence history matching computational cost realization Reynolds base case global-dgn rml method production data algorithm green curve Bayesian Inference Upstream Oil...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Conference, February 20–22, 2017
Paper Number: SPE-182693-MS
... machine learning history matching reservoir simulation approximation ensemble smoother inverse problem square problem ensemble member outlier Bayesian Inference objective function model parameter assumption algorithm iglesia regularization parameter ensemble iteration Reynolds...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Symposium, February 23–25, 2015
Paper Number: SPE-173298-MS
... point surrogate model parameter point history matching prediction gmm distribution uncertainty quantification Upstream Oil & Gas proposal sample point algorithm Bayesian Inference gp surrogate model parameter production history posterior PDF Introduction History matching...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Symposium, February 23–25, 2015
Paper Number: SPE-173192-MS
... Bayesian Inference incorrect facies production data sand facies formulation Introduction Challenges for History Matching of Chanellized Reservoirs A reservoir model usually consists of gridblock-based rock properties (permeability, porosity, net-to-gross ratio, initial water saturation, etc...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Symposium, February 18–20, 2013
Paper Number: SPE-163656-MS
... Intelligence Upstream Oil & Gas information parameterization unconditional realization uncertainty quantification reservoir property realization Bayesian Inference Jafarpour inverse problem representation unconditional sample sample mean geological modeling formulation reservoir...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Symposium, February 18–20, 2013
Paper Number: SPE-163663-MS
... in their work that complex geological structures can be effectively decomposed into lower dimension by mapping the random field into feature space. Markov Chain Monte Carlo (MCMC) methods are often used to probe the posterior probability distribution in Bayesian inference inverse problems. Many Markov chain...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Symposium, February 21–23, 2011
Paper Number: SPE-141336-MS
... uncertainty in the predicted cumulative oil and water production. bayesian inference objective function reservoir simulation localization vector markov chain artificial intelligence upstream oil & gas model parameter reynolds algorithm matrix relative freq enkf covariance localization...
Proceedings Papers

Paper presented at the SPE Reservoir Simulation Symposium, February 2–4, 2009
Paper Number: SPE-118818-MS
... information History Bayesian Inference proposal distribution model parameter learning-based vfsa iteration parallel learning reservoir model pilot point parameterization conventional vfsa Stoffa distribution function inversion reservoir parameter VFSA Introduction A reservoir model...

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